This course is an introduction to how to use relational databases in business analysis. You will learn how relational databases work, and how to use entity-relationship diagrams to display the structure of the data held within them. This knowledge will help you understand how data needs to be collected in business contexts, and help you identify features you want to consider if you are involved in implementing new data collection efforts. You will also learn how to execute the most useful query and table aggregation statements for business analysts, and practice using them with real databases. No more waiting 48 hours for someone else in the company to provide data to you – you will be able to get the data by yourself!
By the end of this course, you will have a clear understanding of how relational databases work, and have a portfolio of queries you can show potential employers. Businesses are collecting increasing amounts of information with the hope that data will yield novel insights into how to improve businesses. Analysts that understand how to access this data – this means you! – will have a strong competitive advantage in this data-smitten business world.

AZ

Great course! It takes you from zero knowledge of SQL to being able to write quite complicated queries, and being ready for most of standard SQL questions in job interviews. Strongly recommended!

PI

Dec 26, 2017

Filled StarFilled StarFilled StarFilled StarFilled Star

I recommend this course although the exercise requires more time than the average courses in Coursera. If you complete it seriously on your own you will learn a lot in order to apply it at work.

从本节课中

Queries to Address More Detailed Business Questions

<p>Welcome to week 4, the final week of Managing Big Data with MySQL! This week you will practice integrating the SQL syntax you’ve learn so far into queries that address analysis questions typical of those you will complete as a business data analyst.</p> <p>By the end of the week, you will be able to:</p><ul><li>Design and execute subqueries</li><li>Introduce logical conditions into your queries using IF and CASE statements</li><li>Implement analyses that accommodate missing data or data mistakes, and</li><li>Write complex queries that incorporate many tables and clauses.</li></ul><p>By the end of this week you will feel confident claiming that you know how to write SQL queries to create business value. Due to the extensive nature of the queries we will practice this week, we have put the graded quiz that tests your understanding of the SQL strategies you will practice in its own week rather than including it in this week’s materials. </p> <p>Make sure to complete both the MySQL exercises and the Teradata exercises, and we strongly encourage you to use the course Discussions to help each other with questions. </p><p>To get started, please begin with the video 'Welcome to Week 4.’</p><p>I hope you enjoy this week’s materials!</p>

教学方

Daniel Egger

Executive in Residence and Director, Center for Quantitative Modeling

Jana Schaich Borg

Assistant Research Professor

脚本

Welcome to the final week of Managing Big Data with MySQL and Teradata. You have done a terrific job working through all the exercises that teach you how to write SQL queries. This week we are going to learn a couple of additional tools that will make it easier for you to write queries that extract the specific data you want. The first thing you are going to learn is how to write subqueries. Subqueries, also known as inner queries, or nested queries, are a mechanism for breaking up the operations in an overall query into separate steps. By doing this, subqueries help solve a lot of problems we encounter with aggregation functions and joins, and sometimes provide us with more elegant ways to represent the logic behind our queries. You'll see that the first trick to subqueries is making sure you format them so that it's easy to see which parts of the query will be executed together. The second trick is to write and interpret the subquery starting with the innermost query first, working your way out step by step to the outermost query. You will already know how this works after completing the first exercise of this week. After that, we will learn about a couple other logical functions that you might want to use in your analysis of business data. Then in the last phase of this week's assignments, we're going to talk about how to translate your analysis objectives into questions that can be addressed through queries. The first thing you need to do in order to accomplish these objectives is figure out the right questions to ask, and come up with a plan about how you're going to answer those questions efficiently. Here's Elliot Cohen again, producer at Dognition, giving us his opinion about how important this part of the analysis process is. >> The most important thing that we found is that you have to go into every test with a question. You need to have a hypothesis, and you need to know exactly what you're doing to test that. Because if you're just going in and looking, either you're going to find things that don't matter, which is useless. Or you're not going to find anything which is equally useless. So find a testable hypothesis before you go in, is the only really important thing I'd say. >> We are going to talk about resources you can use to design an analysis plan based on specific hypotheses and questions. Then we're going to use the analysis plan we've created for our Dognition project to practice turning business questions into SQL queries. Many of the questions we will ask about Dognition users would be similar to the questions business analysts at Box ask about their users. Here's Ryan Lueke again. >> Yes, our business analysts use SQL to query data that we have about how users use Box. So both usage patterns, like, how active are our users? How many active 30 day users do we have or 7 day? Or how many pieces of content do they upload per week? Or are they active mostly on weekdays or weekends? Based on their locale, what sort of collaboration do they do? How about the difference between how users in our free tier operate versus how users in our business or enterprise class tiers operate? >> You will address questions that are very similar to these in the exercises you will complete this week. I think one of the hardest parts about learning SQL is figuring out how to translate the words you would use to describe the analytical results you know you want to achieve, into actual SQL query language on a screen. The best way to do that is through practice writing queries that are specifically designed to help you analyze and interpret the data you have in front of you. So you will start that practice using queries related to our Dognition analysis plan, which you will go through step by step. Then you will answer many similar queries using the Dillard's data set. In essence, we're going to practice, practice, practice, and then practice some more. By the end, you will feel confident claiming that you know how to write SQL queries to create business value. Let's jump in and start, shall we?